Minimal clinically important difference (MCID), substantial clinical benefit (SCB), and patient-acceptable symptom state (PASS) in patients who have undergone total knee arthroplasty: a systematic review
Bibliographic record
Abstract
BACKGROUND: The present systematic review investigated the minimal clinically important difference (MCID), substantial clinical benefit (SCB), and patient-acceptable symptom state (PASS) of several frequent and established PROMs used to assess patients who have undergone TKA. This study was conducted according to the 2020 PRISMA statement. METHODS: In September 2023, PubMed, Web of Science, and Embase were accessed with no time constraint All clinical studies investigating tools to assess the clinical relevance of PROMs used to evaluate patients having received TKA were accessed. Only studies which evaluated the MCID, PASS, or SCB were eligible. The PROMs of interest were the Forgotten Joint Score-12 (FJS-12), the Oxford Knee Score (OKS), the Knee Injury and Osteoarthritis Outcome Score (KOOS) and its related subscales activity of daily living (ADL), pain, quality of life (QoL), sports and recreational activities, and symptoms, the Western Ontario and McMaster Universities Osteoarthritis (WOMAC) score, the Knee Society Score (KSS) and related function score, and the Short Form-12 (SF-12) and Short Form-36 (SF-36). RESULTS: Data from 29,737 patients were collected. The overall risk of bias was low to moderate. The great variability of thresholds for MCID, SCB and PASS between questionnaires but also between investigated aspects was noted, whereby MCIDs for the SF-36 appear lower than for knee-specific questionnaires. CONCLUSION: Despite its critical role from a patient's perspective, the dimension of SCB is still neglected in the literature. Moreover, thresholds for the different concepts need to be condition-specific. We encourage authors to specifically report such data in future studies and to adhere to previously reported definitions to allow future comparison. Level of evidence Level IV, systematic review and meta-analysis.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.025 | 0.105 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.012 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".